the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the equator
Magdalena Pieler
Gottfried Kirchengast
Abstract. Globally available and highly vertical resolved wind fields are crucial for the analysis of atmospheric dynamics for the benefit of climate studies. Most observation techniques have problems to fulfill both requirements. Especially in the tropics and in the southern hemisphere more wind data availability is required. In this study we investigate the potential of radio occultation (RO) data for climate-oriented wind field monitoring in the tropics, with a specific focus on the equatorial area between ±5° latitude. In this region, the geostrophic balance breaks down, due to the Coriolis force term approaching zero. One further aim is to understand how the individual wind components of the geostrophic balance and equatorial balance approximations bridge across the equator and where each component breaks down. We analyze the equatorial balance equation within this latitude band. In a wider range over the tropics, we derive the RO wind fields also using the geostrophic approximation and we compared the RO winds with ERA5 data. From analyzing first the zonal and meridional wind component, we find that the meridional wind component is more volatile in its derivation, however the total wind speed benefits from a computation of both wind components. Investigating next the bias between the RO and ERA5 computed winds, we find that the systematic data bias is smaller than the bias resulting from the approximation itself. As a final aspect we inspected the monthly-mean RO wind data over the full example year 2009. The bias in the upper troposphere and lower stratosphere is mainly smaller than ±2 m s−1, which is in line with the wind field requirements of the World Meteorological Organization. This is encouraging for the use of RO wind fields in climate monitoring over the entire globe including the equatorial region.
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Julia Danzer et al.
Status: open (until 23 Sep 2023)
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RC1: 'Comment on amt-2023-137', Anonymous Referee #1, 24 Aug 2023
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General commentsThe study described by the manuscript is an interesting and well-designed test of the potential of radio occultation (RO) data for wind field monitoring across the equator where the geostrophic balance breaks down. Two types of bias are investigated: a) biases from the equatorial-balance approximation (referred to as "equatorial-balance bias") by comparing actual and equatorial-balanced wind fields from ERA5 reanalysis data, and b) biases from using RO data (referred to as "systematic data bias") by comparing wind fields from RO and ERA5 obtained by the balance approximation. Key questions addressed are how well the equatorial-balanced winds bridge the geostrophic winds across the equator, and which roles the horizontal wind components, as well as the resulting wind speed, play in the break-down of the geostrophic approximation.
Scientifically, the study presented is perhaps not a major leap forward, but it is a well-designed study, it fills a gap in the literature, it is well-written and easy to follow and it provides practically useful information. For anyone interested in generating atmospheric wind fields from RO data, this paper will provide highly valuable information.
The manuscript is well worth to be published. However, before accepting the manuscript for publication, I would like to see some questions clarified. See the specific comments and questions below. Addressing these questions is essential to fully understand some of the issues discussed in the manuscript, and addressing them will certainly improve the manuscript.
Specific comments and questions1) Equations 1 and 2: what, precisely, are the variables x and y? I would like to see a level of detail here corresponding to that provided for Equations 3 and 4. Also, latitude is used in Equations 1 and 2 before it is introduced in association with Equations 3 and 4.
2) RO data retrievals: The key variable used in the study is geopotential height as a function of pressure (or pressure as a function of geopotential height). How is pressure retrieved? It is mentioned that the RO geopotential climatologies are available from 1000 hPa to 5 hPa. That covers atmospheric regions where the "dry" approximation is applicable as well as regions where it is certainly not applicable. Some explanations of how that is handled is needed.3) You mention that the monthly-mean RO data at the 2.5x2.5 degree grid points are computed by "Gaussian latitude-longitude weighting" within a radius of 600 km. What is the width of the Gaussian? Is it 600 km? Or is 600 km the distance from the grid point within which the profiles contributes to the grid point mean?
4) You mention the need to further average to a 5x5 degree grid for the equatorial-balance calculation. Did you try other differencing techniques than forward finite-differences? It may be to simplistic, and other differencing schemes may be more suitable.
5) In Section 4, the analyses and discussions related to the RO data are focused on three atmospheric layers: 10 hPa, 50 hPa, and 200 hPa. However in Figures 5 and 6, RO data down to 1000 hPa is shown. Whether it makes sense to show RO data in the lower troposphere depends on how the RO data were retrieved. Depending on the answers to comment 2 above, you should consider not to show the full vertical span down to 1000 hPa.
6) Related to comment 5, there is a sentence in Section 4.3 which I don't know how to interpret (lines 259-260): "the larger influence of moisture leads to a higher need of background information in the RO retrieval chain, and as a consequence to an increase in the bias". Is this an indication that you use the "dry" solution all the way down to 1000 hPa?
Citation: https://doi.org/10.5194/amt-2023-137-RC1
Julia Danzer et al.
Julia Danzer et al.
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